{"id":"W2262384175","doi":"","title":"Pedestrian Fatality Data Quality: Problems and Definitions","year":2016,"lang":"en","type":"article","venue":"Transportation Research Board 95th Annual MeetingTransportation Research Board","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Pedestrian; Quarter (Canadian coin); Transport engineering; Data quality; Data collection; Quality (philosophy); Business; Engineering; Geography; Operations management","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.2330454,0.0008852531,0.001973114,0.01722021,0.004139142,0.009682435,0.008029833,0.003144988,0.001784233],"category_scores_gemma":[0.4853729,0.001295787,0.001602598,0.02412812,0.008822306,0.01163095,0.008303648,0.005754515,0.0005594504],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01284713,"about_ca_system_score_gemma":0.01342761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02849924,"about_ca_topic_score_gemma":0.01397848,"domain_scores_codex":[0.6323453,0.1959941,0.08111604,0.01625527,0.07109496,0.003194388],"domain_scores_gemma":[0.3399554,0.4194978,0.0634798,0.04780094,0.1254252,0.003840685],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"observational","study_design_scores_codex":[0.0003394523,0.000171274,0.2283957,0.005486919,0.0004804445,0.000421522,0.01586592,0.004660998,0.0003722568,0.3104878,0.128858,0.3044597],"study_design_scores_gemma":[0.0001491741,0.0002968114,0.1195421,0.02509354,0.0003784701,0.002758697,0.0214402,0.02229946,0.002307079,0.3500982,0.4551469,0.0004894736],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06604806,0.05926371,0.5542154,0.2403205,0.007339527,0.003466815,0.0268388,0.001199695,0.04130755],"genre_scores_gemma":[0.5918574,0.02044368,0.3034717,0.04799728,0.005298591,0.006616809,0.01930853,0.0006776859,0.004328229],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7669546,"threshold_uncertainty_score":0.9457915,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2357836064950796,"score_gpt":0.3954824599312563,"score_spread":0.1596988534361767,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}